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hrenWaC

The Croatian-English Parallel Web Corpus - The parallel document pair candidates were automatically extracted from the hrWaC corpus by Nikola Ljubešić. These candidates were manually checked by Daša Berović and Danijela Merkler under the supervision of Marko Tadić. The collection is available from http://www.nljubesic.net/resources/corpora/hrenwac provided under the CC-BY-SA license

2 languages, total number of files: 2
total number of tokens: 4.96M
total number of sentence fragments: 0.20M

Please cite the following article if you use any part of the corpus in your own work:
Jörg Tiedemann, 2009, News from OPUS - A Collection of Multilingual Parallel Corpora with Tools and Interfaces. In N. Nicolov and K. Bontcheva and G. Angelova and R. Mitkov (eds.) Recent Advances in Natural Language Processing (vol V), pages 237-248, John Benjamins, Amsterdam/Philadelphia

Download

Complete download (XML): hrenWaC1.tar.gz (48M )

Bottom-left triangle: download files
  • ces = sentence alignments in XCES format
  • leftmost column language IDs = corpus files in XML
  • TMX and plain text files (Moses): see "Statistics" below
  • lower row language IDs = parsed corpus files (if they exist)
Upper-right triangle: sample files
  • view = bilingual XML file samples
  • upper row language IDs = monolingual XML file samples
  • rightmost column language IDs = parsed XML file samples (if they exist)

en hr
en viewen
hr ces hr
en hr

Statistics and TMX/Moses Downloads

Number of files, tokens, and sentences per language (including non-parallel ones if they exist)
Number of sentence alignment units per language pair

Upper-right triangle: download translation memory files (TMX)
Bottom-left triangle: download plain text files (MOSES/GIZA++)

language files tokens sentencesenhr
en1 2.6M 99.0k96.4k
hr1 2.3M 99.0k99.0k

Note that TMX files only contain unique translation units and, therefore, the number of aligned units is smaller than for the distributions in Moses and XML format. Moses downloads include all non-empty alignment units including duplicates. Token counts for each language also include duplicate sentences and documents.